Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.7 (Adaptive)
90
DeepSeek V4 Pro Base
43
Verified leaderboard positions: Claude Opus 4.7 (Adaptive) #5 · DeepSeek V4 Pro Base unranked
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Reasoning
+24.3 difference
Knowledge
+4.8 difference
Claude Opus 4.7 (Adaptive)
DeepSeek V4 Pro Base
$5 / $25
$null / $null
N/A
N/A
N/A
N/A
1M
1M
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. DeepSeek V4 Pro Base only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Claude Opus 4.7 (Adaptive) is clearly ahead on the provisional aggregate, 90 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.7 (Adaptive)'s sharpest advantage is in reasoning, where it averages 75.8 against 51.5.
Claude Opus 4.7 (Adaptive) is the reasoning model in the pair, while DeepSeek V4 Pro Base is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.
Claude Opus 4.7 (Adaptive) is ahead on BenchLM's provisional leaderboard, 90 to 43.
Claude Opus 4.7 (Adaptive) has the edge for knowledge tasks in this comparison, averaging 68.2 versus 63.4. DeepSeek V4 Pro Base stays close enough that the answer can still flip depending on your workload.
Claude Opus 4.7 (Adaptive) has the edge for reasoning in this comparison, averaging 75.8 versus 51.5. DeepSeek V4 Pro Base stays close enough that the answer can still flip depending on your workload.
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